{"as_of":"2026-08-20T16:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ec5b22a7c518f0d4cd212de7a0fc2d3e943b9ee2e0cdfaae52030802b50e8db5","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T19:40:06.710707Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-11T19:40:06.765973Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1706.04737","last_updated":"2017-06-15T05:01:53Z","snapshot_observed_at":"2026-08-14T20:53:56.423656Z","submitted_at":"2017-06-15T05:01:53Z","title":"Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":"1706.04737","doi":null,"metadata_source":"pith","pith_arxiv_id":"1706.04737","snapshot_observed_at":"2026-08-11T19:40:06.765973Z","title":"Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation","venue":"cs.CV","work_id":"319479a1-7d8d-471b-bc15-f1afdec93828","year":2017},"citing_paper":{"arxiv_id":"2412.06470","last_updated":"2025-03-17T00:35:34Z","snapshot_observed_at":"2026-08-17T14:41:02.099671Z","submitted_at":"2024-12-09T13:15:52Z","title":"Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T19:40:06.710707Z"},"links":{"cited_paper":"/paper/1706.04737","citing_paper":"/paper/2412.06470"},"observation_digest":"sha256:319bc30db730c8718a21d29ae89ef65e92e57c0d4f3df6967ac0b47fd22b35a6","observation_id":"fcca782b-ebe3-4033-a54c-012ac166ca40","resolution":{"observed_at":"2026-08-11T19:40:06.774342Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1706.04737/citation-record","integrity":"/paper/1706.04737/integrity","json":"/paper/1706.04737/citation-record.json","paper":"/paper/1706.04737"},"outbound":[],"paper":{"arxiv_id":"1706.04737","last_updated":"2017-06-15T05:01:53Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T20:53:56.423656Z","submitted_at":"2017-06-15T05:01:53Z","title":"Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1706.04737."}